code: def __init__(self, mean, crop_size):
      self.mean = mean
      self.crop_size = crop_size
  
      ch_mean = np.average(mean, axis=(1, 2))
      perturbation = (mean - ch_mean.reshape(3, 1, 1)) / 255.0
      perturbation = perturbation[:3, :crop_size, :crop_size].astype(
          chainer.get_dtype()
      )
      self.perturbation = perturbation.reshape(
          1, 3, crop_size, crop_size
      )
  
file_path: chainer/examples/imagenet/dali_util.py
imports: import numpy
  import chainer
  from chainer.backends import cuda
  import ctypes
label_desc: Use image node_id 1 to create a new DaliConverter object from inherited base classes: object with example: obj = DaliConverter(mean, crop_size)